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Record W2899146640 · doi:10.23919/ipec.2018.8507547

On-board Single-Phase Electric Vehicle Charger with Active Front End

2018· article· en· W2899146640 on OpenAlexaff
Theodore Soong, Peter W. Lehn

Bibliographic record

Venue2018 International Power Electronics Conference (IPEC-Niigata 2018 -ECCE Asia) · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDrivetrainInverterAutomotive engineeringAC powerElectric vehicleElectrical engineeringTraction motorThree-phaseHarmonicComputer scienceVoltagePower (physics)TorqueEngineeringPhysics

Abstract

fetched live from OpenAlex

Mass adoption of electric vehicles (EVs) is contingent on the availability of charging infrastructure. One solution to this issue is the introduction of on-board chargers, but such solutions typically require the installation of additional magnetic components that increase EV mass. An alternative approach is the dynamic re-deployment of drivetrain components for stationary charging. This work proposes an on-board single-phase charger that re-uses the traction inverter and motors. The system consists of a dual inverter drivetrain, which affords higher voltage charging compared to other systems. In addition, the system is able to operate bidirectionally and operate at any power factor for grid support services with real and reactive power without subjecting the motor to low frequency harmonic currents. The principle of operation and control of the proposed system is presented and demonstrated by simulation results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.281
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2018
Admission routes1
Has abstractyes

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